Soil moisture is a critical component of the soil-plant-atmosphere continuum(SPAC)in fruit trees.However,highprecision monitoring of orchard soil moisture at the regional scale still remains a challenge.This study pre...Soil moisture is a critical component of the soil-plant-atmosphere continuum(SPAC)in fruit trees.However,highprecision monitoring of orchard soil moisture at the regional scale still remains a challenge.This study presents a two-stage feature space model to estimate root zone soil moisture using UAV remote sensing data.The results indicate that the temperature-leaf area index(TLDI)is negatively correlated with soil water content.The upper triangular space performs highly effectively for deep soil moisture inversion,with R2 values ranging from 0.56 to 0.66,RMSE between 0.20 and 0.27,and RPD from 1.25 to 1.50.Conversely,the lower triangular space yields superior results for shallow soil moisture inversion,with R2 values between 0.67 and 0.82,RMSE from 0.15 to 0.19,and RPD between 1.67 and 2.09.The results suggest that the lower triangular space is optimal for shallow soil moisture inversion,while the upper triangular space is more suited for deep soil moisture inversion.This study presents a novel approach for estimating deep soil moisture in orchards,providing a theoretical basis for improving soil moisture management.展开更多
As a crucial fruit tree crop,the health and yield of apple trees are intricately linked to soil moisture conditions.This study aimed to integrate the enhanced WOFOST model with the HYDRUS model to simulate the growth ...As a crucial fruit tree crop,the health and yield of apple trees are intricately linked to soil moisture conditions.This study aimed to integrate the enhanced WOFOST model with the HYDRUS model to simulate the growth and development of apple trees,as well as the dynamics of soil moisture under varying degrees of water deficit.The outputs of evapotranspiration(ET0)and leaf area index(LAI)from the WOFOST model during the apple growth phase were specifically integrated with HYDRUS-1D.These parameters served as intermediaries to assess the impact of different water deficit scenarios on apple tree growth and soil moisture content.The experimental design included three levels of water deficit treatments in addition to control,with irrigation volumes for the deficit treatments set at 85%,70%,and 55%of the control’s volume,respectively.The model-predicted LAI across all irrigation treatments exhibited an R^(2) range of 0.89-0.95,a normalized root mean square error(NRMSE)between 8.02%and 14.57%,and yield prediction errors ranging from 6.27%to 9.61%,closely aligned with empirical data.The accuracy of simulated soil moisture content was enhanced in the 0-30 cm layer,with a slight decrease in accuracy observed in the 30-60 cm layer.For each irrigation treatment,the R^(2) values for simulated soil moisture content ranged from 0.77 to 0.89 in the 0-30 cm layer and from 0.75 to 0.81 in the 30-60 cm layer.This study validated the capability of the WOFOST-HYDRUS model to accurately simulate the effects of varied water deficit treatments on soil moisture,LAI,and apple tree yield,providing valuable insights for developing optimal irrigation strategies.展开更多
基金the funding provided by the National Key Research and Development Program of China(2021YFC3200201)the National Natural Science Foundation of China(52121006,U2240203,and 51779144)+2 种基金the Second Tibetan Plateau Scientific Expedition and Research(2019QZKK0203)the Fundamental Research Funds for the Central Universities of China(B210204015 and B210204014)the Consulting Research Project of Chinese Academy of Engineering(2020-ZD-20 and 2021-ZD-CQ-2)。
基金supported by the National Natural Science Foundation of China(Grant No.52309050)Key R&D and Promotion Projects in Henan Province(Science and Technology Development)(Grant No.232102110264)+2 种基金Key Scientific Research Projects of Colleges and Universities in Henan Province(Grant No.24B416001)Youth Backbone Teacher Project of Henan University of Science and Technology(Grants No.13450013 and 13450010)Sichuan Province Science and Technology Support Projects(Grants No.2023YFQ0025,2024YFHZ0217,2024ZHCG0101,2024YFHZ0200).
文摘Soil moisture is a critical component of the soil-plant-atmosphere continuum(SPAC)in fruit trees.However,highprecision monitoring of orchard soil moisture at the regional scale still remains a challenge.This study presents a two-stage feature space model to estimate root zone soil moisture using UAV remote sensing data.The results indicate that the temperature-leaf area index(TLDI)is negatively correlated with soil water content.The upper triangular space performs highly effectively for deep soil moisture inversion,with R2 values ranging from 0.56 to 0.66,RMSE between 0.20 and 0.27,and RPD from 1.25 to 1.50.Conversely,the lower triangular space yields superior results for shallow soil moisture inversion,with R2 values between 0.67 and 0.82,RMSE from 0.15 to 0.19,and RPD between 1.67 and 2.09.The results suggest that the lower triangular space is optimal for shallow soil moisture inversion,while the upper triangular space is more suited for deep soil moisture inversion.This study presents a novel approach for estimating deep soil moisture in orchards,providing a theoretical basis for improving soil moisture management.
基金financially supported by the National Natural Science Foundation of China(Grant No.52309050)the Key R&D and Promotion Projects in Henan Province(Science and Technology Development)(Grant No.232102110264)+1 种基金Youth Backbone Teacher Project of Henan University of Science and Technology(Grants No.13450013 and 13450010)the Key Scientific Research Projects of Colleges and Universities in Henan Province(Grant No.24B416001).
文摘As a crucial fruit tree crop,the health and yield of apple trees are intricately linked to soil moisture conditions.This study aimed to integrate the enhanced WOFOST model with the HYDRUS model to simulate the growth and development of apple trees,as well as the dynamics of soil moisture under varying degrees of water deficit.The outputs of evapotranspiration(ET0)and leaf area index(LAI)from the WOFOST model during the apple growth phase were specifically integrated with HYDRUS-1D.These parameters served as intermediaries to assess the impact of different water deficit scenarios on apple tree growth and soil moisture content.The experimental design included three levels of water deficit treatments in addition to control,with irrigation volumes for the deficit treatments set at 85%,70%,and 55%of the control’s volume,respectively.The model-predicted LAI across all irrigation treatments exhibited an R^(2) range of 0.89-0.95,a normalized root mean square error(NRMSE)between 8.02%and 14.57%,and yield prediction errors ranging from 6.27%to 9.61%,closely aligned with empirical data.The accuracy of simulated soil moisture content was enhanced in the 0-30 cm layer,with a slight decrease in accuracy observed in the 30-60 cm layer.For each irrigation treatment,the R^(2) values for simulated soil moisture content ranged from 0.77 to 0.89 in the 0-30 cm layer and from 0.75 to 0.81 in the 30-60 cm layer.This study validated the capability of the WOFOST-HYDRUS model to accurately simulate the effects of varied water deficit treatments on soil moisture,LAI,and apple tree yield,providing valuable insights for developing optimal irrigation strategies.
